Abstract Remanent polarization and coercive field in ferroelectrics are often predicted to be high, yet experimentally observed to be much lower-an inconsistency that hinders the rational design of functional materials and devices. We identify a hidden mechanism underlying this discrepancy: the interaction between polarization domain walls (PDWs) and lattice domain walls (LDWs) that standard models omit. Using κ-Ga 2 O 3 as a representative ferroelectric, we develop a machine-learning potential trained on ab initio molecular-dynamics data to capture realistic polarization switching. Our simulations reveal that PDWs become topologically blocked at 120° LDWs, stabilizing residual domain-wall networks that suppress remanent polarization while enabling rapid, low-field switching by bypassing slow nucleation. The blocking strengthens as lattice domains shrink, offering a new strategy for tuning ferroelectric performance through lattice-domain engineering. The mechanism not only reconciles theoretical with experimental results but also provides a practical approach for improving ferroelectric performance.
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Yonghao Zhu
Wenhao Liu
Run Long
npj Computational Materials
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Zhu et al. (Fri,) studied this question.
www.synapsesocial.com/papers/69abc1845af8044f7a4ea366 — DOI: https://doi.org/10.1038/s41524-026-02022-z